No More Porting: Coding for GPUs with Standard C++, Fortran, and Python

CUDA C++, CUDA Fortran, and OpenACC are hugely successful approaches to GPU programming, but wouldn’t it be nice to write an application that can run on GPUs and multicore CPUs out of the box, without any additional APIs? The parallelism features available in ISO C++ and ISO Fortran enable developers to write their codes such that the baseline code is parallel and ready to run on any parallel platform they encounter. Using libraries like cuNumeric, Python developers can write to standard APIs like NumPy and scale to a full data center. We'll demonstrate the current state-of-the-art in writing application code that is parallel and ready to run on GPUs, CPUs, and more, using only C++, Fortran, and Python. See what’s possible and learn best practices in writing parallel code with standard language parallelism.